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Michael Miller is the Director of the Department of Biomedical Engineering, a University Gilman Scholar and is the Herschel and Ruth Seder Professor of Biomedical Engineering. Dr. Miller directs the Center for Imaging Science and is the Co-Director of the Kavli Neuroscience Discovery Institute. He received his PhD in biomedical engineering from Johns Hopkins University.

Miller’s early doctoral work in Neuroscience on neural codes in the Auditory system in the Neural Encoding Laboratory[15] at Johns Hopkins University during the Johnson, Mountcastle, Sachs and Young era. Miller focussed on rate-timingpopulation codes in the primary auditory-nerveof complex, speech features including voice-pitch[20] and consonant-vowel syllables.[21] Such neural codes were part of the basis for the discussions at the 1982 New York Academy of Science[22] meeting on efficacy and timeliness of neuroengineered Cochlear implants.

During the 90's, Miller joined the Pattern Theory group at Brown University to work with Ulf Grenander on problems in image analysis based on Markov random fields. Grenander and Miller collaborated for two decades working on human shape and form during which time Miller remained a visiting Professor within the Pattern Theory group of the Division of Applied Mathematics at Brown University. They published together several influential papers on Computational anatomy as a formal theory of human shape and form.[31][32][33] By 2005, the Computational anatomy framework establishing high-dimensional brain mapping via diffeomorphisms had become the de facto standard for cross-sectionl analyses of populations studied at the morphological scale of MRI. Computational codes now exist for diffeomorphic template or atlas mapping, including ANTS,[35] DARTEL,[36] DEMONS,[37], LDDMM,[38] and StationaryLDDMM,[39] all actively used codes for constructing correspondences between coordinate systems based on sparse features and dense images.

During these years, Miller and Csernansky [45] had developed a long-term research effort on neuroanatomical phenotyping of Alzheimer's disease, Schizophrenia and mood disorder. In 2005, they published with John Morris an early work on predicting conversion to Alzheimer's disease based on clinically available MRI measurements using the diffeomorphometry technologies.[46] In 2009, the Johns Hopkins University BIOCARD[48] project was initiated, led by Marilyn Albert,[49] to study preclinical Alzheimer's disease. In 2014, the BIOCARD team with Younes demonstrated that the original Braak staging of earliest change associated to the entorhinal cortex in the medial temporal lobe could be demonstrated via diffeomorphometry methods in the population of clinical MRI's,[50] and subsequently that this could be measured via MRI in clinical populations upwards of 10 years before clinical symptom.[51] This has the potential to impact clinical treatment of the disease.

Mission

To advance neuroscience discovery by uniting
neuroscience, engineering and computational data science
to understand the structure and function of the brain.